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Where we analyse the effect of a factor on local diversity

Author: Adrien Taudière

Date: December 3, 2024

See the documentation of the MiscMetabar package for example of alpha diversity analysis.

Code
if(base::interactive()) {
  params <- rmarkdown::yaml_front_matter(here::here("analysis/03_beta_diversity.qmd"))$params
}
factor_of_interest <- params$factor_of_interest
Code
library(knitr)
library(targets)
library(MiscMetabar)
here::i_am("analysis/02_alpha_diversity.qmd")
source(here::here("R/styles.R"))
Code
d_pq <- clean_pq(tar_read("d_vs", store=here::here("_targets/")))
Cleaning suppress 2 taxa and 12 samples.
Code
hill_pq(d_pq, factor_of_interest, one_plot = TRUE) &
  (
    theme_idest(
      subtitle_size = 8,
      plot_title_size = 12,
      plot_margin = margin(5, 10, 5, 10),
      axis_title_size = 9,
      axis_text_size = 8
    ) + theme(legend.position = "none")
  ) 
Taxa are now in rows.

Code
ggbetween_pq(d_pq, factor_of_interest)
$plot_Hill_0


$plot_Hill_1


$plot_Hill_2

Session Information

Session information are detailed below. More information about the machine, the system, as well as python and R packages, are available in the file data/data_final/information_run.txt .

Code
sessionInfo()
R version 4.4.2 (2024-10-31)
Platform: x86_64-pc-linux-gnu
Running under: Debian GNU/Linux 12 (bookworm)

Matrix products: default
BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.11.0 
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.11.0

locale:
 [1] LC_CTYPE=fr_FR.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=fr_FR.UTF-8        LC_COLLATE=fr_FR.UTF-8    
 [5] LC_MONETARY=fr_FR.UTF-8    LC_MESSAGES=fr_FR.UTF-8   
 [7] LC_PAPER=fr_FR.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=fr_FR.UTF-8 LC_IDENTIFICATION=C       

time zone: Europe/Paris
tzcode source: system (glibc)

attached base packages:
[1] stats     graphics  grDevices datasets  utils     methods   base     

other attached packages:
[1] MiscMetabar_0.10.1 purrr_1.0.2        dplyr_1.1.4        dada2_1.34.0      
[5] Rcpp_1.0.13-1      ggplot2_3.5.1      phyloseq_1.50.0    targets_1.9.0     
[9] knitr_1.49        

loaded via a namespace (and not attached):
  [1] RColorBrewer_1.1-3          rstudioapi_0.17.1          
  [3] jsonlite_1.8.9              datawizard_0.13.0          
  [5] correlation_0.8.6           magrittr_2.0.3             
  [7] SuppDists_1.1-9.8           farver_2.1.2               
  [9] rmarkdown_2.29              zlibbioc_1.52.0            
 [11] vctrs_0.6.5                 multtest_2.62.0            
 [13] memoise_2.0.1               Rsamtools_2.22.0           
 [15] paletteer_1.6.0             effectsize_0.8.9           
 [17] htmltools_0.5.8.1           S4Arrays_1.6.0             
 [19] BWStest_0.2.3               Rhdf5lib_1.28.0            
 [21] SparseArray_1.6.0           rhdf5_2.50.0               
 [23] htmlwidgets_1.6.4           plyr_1.8.9                 
 [25] cachem_1.1.0                GenomicAlignments_1.42.0   
 [27] igraph_2.1.1                lifecycle_1.0.4            
 [29] iterators_1.0.14            pkgconfig_2.0.3            
 [31] Matrix_1.7-1                R6_2.5.1                   
 [33] fastmap_1.2.0               PMCMRplus_1.9.12           
 [35] GenomeInfoDbData_1.2.13     MatrixGenerics_1.18.0      
 [37] BayesFactor_0.9.12-4.7      digest_0.6.37              
 [39] colorspace_2.1-1            ShortRead_1.64.0           
 [41] rematch2_2.1.2              patchwork_1.3.0            
 [43] S4Vectors_0.44.0            ps_1.8.1                   
 [45] rprojroot_2.0.4             prismatic_1.1.2            
 [47] GenomicRanges_1.58.0        base64url_1.4              
 [49] hwriter_1.3.2.1             vegan_2.6-8                
 [51] labeling_0.4.3              fansi_1.0.6                
 [53] httr_1.4.7                  abind_1.4-8                
 [55] mgcv_1.9-1                  compiler_4.4.2             
 [57] here_1.0.1                  withr_3.0.2                
 [59] backports_1.5.0             BiocParallel_1.40.0        
 [61] performance_0.12.4          ggsignif_0.6.4             
 [63] MASS_7.3-61                 DelayedArray_0.32.0        
 [65] biomformat_1.34.0           permute_0.9-7              
 [67] tools_4.4.2                 ape_5.8                    
 [69] statsExpressions_1.6.1      glue_1.8.0                 
 [71] callr_3.7.6                 nlme_3.1-166               
 [73] rhdf5filters_1.18.0         grid_4.4.2                 
 [75] cluster_2.1.6               reshape2_1.4.4             
 [77] ade4_1.7-22                 generics_0.1.3             
 [79] gtable_0.3.6                tidyr_1.3.1                
 [81] data.table_1.16.2           utf8_1.2.4                 
 [83] XVector_0.46.0              BiocGenerics_0.52.0        
 [85] ggrepel_0.9.6               foreach_1.5.2              
 [87] pillar_1.9.0                stringr_1.5.1              
 [89] splines_4.4.2               lattice_0.22-6             
 [91] gmp_0.7-5                   renv_1.0.11                
 [93] survival_3.7-0              deldir_2.0-4               
 [95] ggstatsplot_0.12.5          tidyselect_1.2.1           
 [97] pbapply_1.7-2               Biostrings_2.74.0          
 [99] IRanges_2.40.0              SummarizedExperiment_1.36.0
[101] stats4_4.4.2                xfun_0.49                  
[103] Biobase_2.66.0              matrixStats_1.4.1          
[105] stringi_1.8.4               UCSC.utils_1.2.0           
[107] yaml_2.3.10                 kSamples_1.2-10            
[109] evaluate_1.0.1              codetools_0.2-20           
[111] interp_1.1-6                tibble_3.2.1               
[113] BiocManager_1.30.25         multcompView_0.1-10        
[115] cli_3.6.3                   RcppParallel_5.1.9         
[117] secretbase_1.0.3            parameters_0.23.0          
[119] munsell_0.5.1               processx_3.8.4             
[121] GenomeInfoDb_1.42.0         zeallot_0.1.0              
[123] coda_0.19-4.1               png_0.1-8                  
[125] parallel_4.4.2              rstantools_2.4.0           
[127] MatrixModels_0.5-3          bayestestR_0.15.0          
[129] latticeExtra_0.6-30         jpeg_0.1-10                
[131] bitops_1.0-9                Rmpfr_1.0-0                
[133] pwalign_1.2.0               mvtnorm_1.3-2              
[135] scales_1.3.0                insight_0.20.5             
[137] crayon_1.5.3                rlang_1.1.4                

Citation

BibTeX citation:
@online{taudière2024,
  author = {Taudière, Adrien},
  title = {Alpha-Diversity},
  date = {2024-12-03},
  langid = {en}
}
For attribution, please cite this work as:
Taudière, Adrien. 2024. “Alpha-Diversity.” December 3, 2024.